Time-of-arrival estimation for blind beamforming

Ad-hoc arrays formed by mobile devices are increasingly available to capture audio and video in social events. Using spatial signal processing algorithms, e.g., beamforming, with microphone signals of such arrays is hindered by the unknown locations of the devices and the lack of temporal synchronization between them. While self-calibration methods can be applied to estimate these missing parameters, they typically impose restrictions and require time to converge. Time difference of arrival (TDOA) values contain source related spatial information, and they have been previously used in source localization and tracking. In this work, relative time-of-arrival (TOA) is proposed to be used for estimating source spatial information. The method is then applied for beamforming using ad-hoc arrays. Simulations and measurements with smartphones are used to test the accuracy of different proposed TOA estimators. Then, speech captured by a smartphone array is beamformed using the TOA estimators. Results show that Kalman filter based TOA steering achieves similar enhancement performance as using the ground truth TOA.